Seeing through transparency in the craft chocolate industry: The what, how, and why of cacao sourcing
Bibliographic record
Abstract
Transparency is a defining feature of the craft chocolate industry, but with the lack of benchmarks or regulations for this budding industry, entrepreneurs and stakeholders interpret and apply transparency in different ways. In general, transparency appears to be motivated by the aim to improve environmental and social outcomes in cacao origins, but with a lack of rigorous scientific evidence attributing transparency to such outcomes, the extent to which society benefits from industry transparency remains unclear. We provide a first step towards understanding the potential impact of transparency by studying how craft chocolate makers define the concept. Specifically, we ask what information is being disclosed, by whom, how, and why. Our practice-based research methods include collaboration with a key actor in the craft chocolate community: The Chocolate Alliance, an industry platform based in the United States. We employed an iterative mixed-methods approach by engaging 67 research participants in a survey and 13 in semi-structured interviews. Our study indicates that while ethical cacao sourcing is a significant motivator for transparency, craft chocolate makers were also driven by product quality and supply chain objectives. Notably, makers prioritized sharing information they believe will resonate with consumers and encourage purchase, challenging the notion that these companies are wholly driven by non-market goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".